[IC] Edge-based Eye Region Detection in Rotated Face using Global Orientation Histogram

Abstract.

Automatic human face analysis and recognition have become one of the most important research topics in robot society, and research on automatic eye region detection has recently attracted a lot of attentions, as the most important feature for human faces is eyes. Although much effect has been spent, the problem of automatic eye region detection is still challenging, as most of the existing methods mainly focus on eye detection in the frontal face without consideration of the factors, such as non-frontal faces and lighting conditions. This paper proposes an eye region detection method in faces rotated around the front-to-back axis called rotated faces, based on edge information that shows fast computational times. The proposed method consists of two steps: making frontal faces, and then detecting eye regions. The rotated angle of face regions can be estimated by analyzing histogram accumulated from edge orientation of the face region, called global orientation histogram. The rotated face can be frontal faces based on the estimated angle, and then the eye regions are detected in frontal face by analyzing edge orientation histogram of components grouping adjacent edges, called local orientation histogram, already verified by experiment of previous works. Experiment results demonstrated the effectiveness of the proposed method using 300 face images provided from THE Weizmann Institute of Science, and achieved precision rates of 83.5% and computational times of 0.5 seconds.
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2007.